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Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective
Amr Ahmed
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Eric Xing
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Paper Details:
Month: October
Year: 2010
Location: Cambridge, MA
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Unsupervised learning of rhetorical structure with un-topic models
Diarmuid Ó Séaghdha
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Simone Teufel
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Bayesian Checking for Topic Models
David Mimno
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David Blei
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Learning Topics and Positions from Debatepedia
Swapna Gottipati
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Minghui Qiu
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Yanchuan Sim
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Jing Jiang
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Noah A. Smith
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Detecting Latent Ideology in Expert Text: Evidence From Academic Papers in Economics
Zubin Jelveh
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Bruce Kogut
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Suresh Naidu
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Multi-view Models for Political Ideology Detection of News Articles
Vivek Kulkarni
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Junting Ye
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Steve Skiena
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William Yang Wang
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Discovering User Interactions in Ideological Discussions
Arjun Mukherjee
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Bing Liu
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Political Ideology Detection Using Recursive Neural Networks
Mohit Iyyer
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Peter Enns
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Jordan Boyd-Graber
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Philip Resnik
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The Media Frames Corpus: Annotations of Frames Across Issues
Dallas Card
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Amber E. Boydstun
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Justin H. Gross
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Philip Resnik
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Noah A. Smith
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Detecting Cross-Cultural Differences Using a Multilingual Topic Model
E.D. Gutiérrez
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Ekaterina Shutova
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Patricia Lichtenstein
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Gerard de Melo
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Luca Gilardi
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Ideological Perspective Detection Using Semantic Features
Heba Elfardy
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Mona Diab
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Chris Callison-Burch
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Unsupervised Part-of-Speech Tagging in Noisy and Esoteric Domains With a Syntactic-Semantic Bayesian HMM
William M. Darling
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Michael J. Paul
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Fei Song
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Hedge Detection as a Lens on Framing in the GMO Debates: A Position Paper
Eunsol Choi
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Chenhao Tan
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Lillian Lee
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Cristian Danescu-Niculescu-Mizil
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Jennifer Spindel
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Topic-Specific Sentiment Analysis Can Help Identify Political Ideology
Sumit Bhatia
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Deepak P
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http://bitterlemons.org/
Field Of Study
Linguistic Trends
Discourse
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Summarization
Approach
Graphical Model
Language
Chinese
Dataset
News
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